Mechanical strain stimulates COPII‐dependent secretory trafficking via Rac1

Abstract Cells are constantly exposed to various chemical and physical stimuli. While much has been learned about the biochemical factors that regulate secretory trafficking from the endoplasmic reticulum (ER), much less is known about whether and how this trafficking is subject to regulation by mechanical signals. Here, we show that subjecting cells to mechanical strain both induces the formation of ER exit sites (ERES) and accelerates ER‐to‐Golgi trafficking. We found that cells with impaired ERES function were less capable of expanding their surface area when placed under mechanical stress and were more prone to develop plasma membrane defects when subjected to stretching. Thus, coupling of ERES function to mechanotransduction appears to confer resistance of cells to mechanical stress. Furthermore, we show that the coupling of mechanotransduction to ERES formation was mediated via a previously unappreciated ER‐localized pool of the small GTPase Rac1. Mechanistically, we show that Rac1 interacts with the small GTPase Sar1 to drive budding of COPII carriers and stimulates ER‐to‐Golgi transport. This interaction therefore represents an unprecedented link between mechanical strain and export from the ER.

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Further information is available in our Guide For Authors: https://www.embopress.org/page/journal/14602075/authorguide We realize that it is difficult to revise to a specific deadline. In the interest of protecting the conceptual advance provided by the work, we recommend a revision within 3 months (1st May 2022). Please discuss the revision progress ahead of this time with the editor if you require more time to complete the revisions. Use the link below to submit your revision: In this manuscript, the authors have investigated whether mechanical signals can impact the early secretory pathway. They show that a mechanical strain obtained by growing cells on micropatterns of different sizes or by biaxial stretching on PDMS membrane increases the number of endoplasmic reticulum exit sites (ERES) and stimulates ER-export of a secretory marker (mannosidase II). They provide evidence that this effect is dependent of a minor pool of Rac1 interacting with Sar1, which is involved in the biogenesis of COPII vesicles. Overall, this is an interesting study that reveals an unexpected role of Rac1. The authors used a wide range of methodological approaches that support such a role. I have a few comments that should be addressed prior to publication: This manuscript reports control of secretory pathway by mechanical cues through a direct interaction of Rac1 and Sar1. This would represent a novel and exciting development in the field. There are many external and intrinsic cues that impact on secretory activity and while perhaps not surprising that mechanical strain plays a role, the mechanism here would provide a rally compelling and exciting advance. Sar1 controls the assembly of the COPII complex at the ER, Rac1 controls multiple levels of actin cytoskeleton remodeling at various points through the cell.
The key to the paper is whether indeed Sar1 and Rac1 do indeed interact and whether mechanical strain does indeed impact COPII function.
The data in Figure 1 seek to define an increase in ERES number caused by cell spreading. While this could be the case, it is equally possible that the pre-existing ERES are less well clustered and therefore more definable using the software. This has been shown previously in work on TFG for example. Indeed, that this change occurs within a small number of hours is challenging to reconcile with enhanced expression of COPII which would presumably be needed to account for this increase in ERES number (as happens for example in plasma cell differentiation).
I think the work suffers from being done in HeLa cells here in which COPII seems very tightly clustered and difficult to resolve in terms of individual puncta. While other cell types have been used to validate outcomes later in the paper, it would be better to see well spread cells here. Also one is left to question the generality given that these are a cancer cell line -is there a relevance to hard versus soft tumors here? I struggled to interpret some of Figure 2 and question the use of statistics here in 2B (my interpretation is that in all cases depletion of Sar1 still reduces cell spread irrespective of micropattern. I think it difficult to conclude that these data support that "the early secretory pathway is required for adaptation to mechanical strain" rather that it suggests the early secretory pathway is required for cell spreading (which is largely considered known from its central role in both matrix biogenesis, integrin trafficking, and general membrane dynamics). Sec16A is used as a key COPII protein here (2C) yet I saw no validation of Sec16A knockdown or indication of how the degree of knockdown is correlated with cell-by-cell outcomes. Incomplete depletion could explain these data.
The Rac inhibition work is questionable from the conclusions drawn, I am not convinced for example that the inhibition f Rac1 activity does indeed reduces ERES number. Also, I was surprised by the apparent reproducibility of some data -e.g. what is the consistent peak of activity at 20 mins in 3E pink line? If these are true averages from independent replicates one would not expect that. I was also not clear if the data in 3G were from stable cell lines -expression levels of such trafficking reporters can have a big impact on trafficking efficiency. Also, for robustness, such data should really include a restoration of function such as RNAi resistant Rac1.
Also in terms of image processing -in "background subtraction" is the same parameter applied to all images in a data set (as it must be) or on a case-by case/per image "auto calculated" basis? If the latter, this will in my view invalidate the data. If uniformly applied how is the background calculated i.e. on which image? I did not find the colocalization data in Figure 4 convincing. Rac1 might be on endosomes at ER-endosome contact sites or at points of actin-ER crossover. Even if one accepts "colocalization" 2 spots with partial overlap seems to low to explain significant impacts on cell function. How does this change under strain? The images also look overly processed -raw data should be made available.
What validation has been done of GFP-Rac1 as a reporter?
In 4G and H again I would like to have been able to review the underpinning data. These changes seem small and no statistical test is applied. No indication is given of reproducibility either.
The KDELR experiments are intriguing but incomplete -surely these need to be linked to assays of Rac activation? Also KDELR2 will cycle from the ER to the Golgi so will not "only act at the ER".
My major concern lies with the interaction data -the modelling is nice but needs experimental support. That shown does not robustly provide this. In Figure 7  Concerns on the statistical data -in every case, the numbers of technical and biological replicates must be stated. In many cases the data are not compelling and "hidden" in histograms when the original data should be included and plots done as scatter/violin/etc. SEM is not appropriate here either -standard deviations should be shown in all cases (see https://rupress.org/jcb/article/177/1/7/34602/Error-bars-in-experimental-biology) The t-test is likely not appropriate at all as most of the data do not look normally distributed. A non-parametric test with multiple comparisons is likely more appropriate.
I am sorry that I cannot be more positive about this work. The topic is very exciting and has significant potential for in vivo relevance. That said, the data do (at least not yet) sufficiently support the conclusions.

Referee #3:
This manuscript from the Farhan group addresses an important question in the secretion field. How cells regulate secretion at the level of ER exit sites (ERES) and other cellular structures remains poorly understood. In fact, even specific conditions that trigger regulation of secretion are not fully catalogued/documented. Mechanical stimulation is known to influence the plasma membrane (and endocytosis), cell growth and motility, all of which depend to some extent on secretion. Here, the authors probe the link between mechanical strain and secretion. The topic is exciting, and the findings are important. The main finding is that ERES abundance does indeed respond to mechanical stress, and that this is dependent on Rac1. The authors go on to show that Rac1 may play a more constitute role in ERES maintenance, and here there is a lost opportunity that would leverage the mechanical strain approaches developed in the first half of the study to reinforce the role for Rac1.
I have several specific criticisms: 1. On p. 3 the authors claim that the observed increase in ERES is not due to increase in volume/biomass. Although I appreciate the short time frame of the experiment, I'm not sure I understand the broader reasoning here. To substantiate this claim, the authors could measure cell volume as well as surface area and ERES number to demonstrate the relationships between these parameters more precisely. 2. Fig. 1E: the FRET sensor would be an excellent reporter to use in large vs. small cells to further substantiate the Rac1 effects. 3. The effect of Sar1 knockdown on cell spreading is profound. I was left wondering why Rac1 inhibition does not similarly cause cells to fully spread, especially if Rac1 activation lies upstream of Sar1 and its role in ERES. 4. The authors go on to show that Rac1 may play a more constitutive role in ERES maintenance/function. Here I felt there is room to leverage the tools to better probe the mechanical effects. For example, does KDELR-GAP overexpression abrogate stretching effects? Similarly, does CytoD/LatA treatment abrogate the stretch response, implying broader stretch effects beyond local Rac1? Finally, do Rac1/Sar1 BiFC puncta increase upon mechanical strain? 5. Controls for the Rac1-Sar1 BiFC experiment are missing (ie no fluorescence when each partner is expressed alone). 6. In Figure 7, the pulldowns showing Rac1/Sar1 interaction, and the "active Sar1" assay should include additional GDP and/or GMP-PNP controls to demonstrate nucleotide specificity.
Minor items: • Figure

Response to the Editorial comments:
Firstly, all reviewers raise important technical concerns about the microscopy workflows used in the study. Here, I can see two particularly important comments: i) the issue of the variation among ratios between fluorescence signals in the RUSH experiments (as raised by reviewer 1 -point 2), Response: We think that there might be a misunderstanding. There is no big variation. In Figure 3G the ratio after 20 min of biotin addition is around 8. In Figure 5G the ratio measured at 20 min after biotin is has a value of 6.5. The end points of both figures are different (20 min in one and 30 min in the other). This might have caused the confusion.
ii) that experimental artifacts may mean that Rac1 inhibition may not actually be causing a reduction ERES number, or that the effect may be cell-line-specific (as raised by reviewer 2paragraphs 3-7). Response: As far as cell line specificity is concerned, we showed already in the previous version that mechanical stimuli and/or Rac1 inhibition affects the number of ERES in HeLa, PC3 and MDA-MB-231 cells. Because all of these cell lines are transformed, we have now used RPE-1 cells (Fig.1C, Fig.S1C-E) and find that ERES in these cells also respond to mechanical stimuli in Rac1-dependent manner. Thus, our observations are not cell line specific. As for the other point raised by reviewer 2, which concerns whether the increase of ERES upon stretching is real, or whether it is simply a redistribution of ERES. We think the increase is genuine for two reasons: firstly, if the increase were not a real one, but only due to redistribution of ERES, then it would be expected to occur in any condition, irrespective of the biological context. However, we observe the increase only in control cells and not in Rac1 inhibited cells. Secondly, the increase of ERES is in line with the acceleration of ER-to-Golgi trafficking as observed in the RUSH assay. A mere redistribution will not cause a change in ER-to-Golgi trafficking. Therefore, we think that our conclusions and interpretations of these data is valid.
Please also reconsider the suitability of all statistical tests that you have used throughout the manuscript. Response: We have now elaborated "Statistical analyses" section in the methods. We have also updated all figure legends to better describe the statistical tests that were used, the number of experiments and the number of cells quantified from each experiment.
Secondly, you should address the question of the persuasiveness of your IP data. All reviewers were concerned about the robustness of your negative controls. Please consider using a control protein which is closer to Rac1 (such as GFP-RhoA), in addition to the constitutively active and dominant negative Rac1 variants. Response: We have performed the coIP with GFP-RhoA as suggested, and did not detect any interaction. These data have now been added to the manuscript (Fig.7F). To further support the Rac1-Sar1 interaction data, we used the computational modeling to predict residues in Rac1 that mediate an interaction with Sar1. We mutated these residues and observed a marked reduction of the interaction (Fig. 7F). Thus, our IP data have now been substantially strengthened. We have refrained from using constitutively active and dominant negative Rac1 variants for reasons specified in response to reviewer #2 (please check the response at the end of p.6-7). Rather, we chose to use GTPgS and GDP as suggested by Reviewer 3. Thirdly, it may be possible, as you address these concerns, to use the tools you have 23rd May 2022 1st Authors' Response to Reviewers already developed to gain a deeper general understanding of the relationship between Rac1 and ERES (as pointed out by reviewer 3 -points 3 and 4). Response: We have addressed both points raised by the reviewer. In point 3, the reviewer asked us to test whether Rac1 inhibition has an impact on cell spreading on large micropatterns. This was indeed the case, and these data are now part of the revised manuscript (Fig.2D&E). In point 4, the reviewer asked for a couple of experiments. On one hand, the reviewer asked us to test whether inhibition of local Rac1 activity at the ER abrogates stretching effects. We tested this by culturing cells that express the ER-anchored Rac1-GAP on Crossbow micropattern, and noted a reduction in ERES only when cells were forced to grow larger (Fig.4G&H, Fig. S4F&G). The reviewer also asked us to test whether actin is involved in mediating the stretch response of ERES under mechanical stimulation. This is a relevant control experiment because we ruled out that actin plays a role in mediating the effect of Rac1 on ERES under standard growth conditions. We have performed the experiment the reviewer asked for and data are presented in Fig.5F&G. We found that actin disruption with cytochalasin D during mechanical strain did not prevent the increase in ERES number. These new data further support the notion that actin does not mediate mechanotransduction signaling to ERES (at least not in the context of our experiments).

Response to Referee #1:
In this manuscript, the authors have investigated whether mechanical signals can impact the early secretory pathway. They show that a mechanical strain obtained by growing cells on micropatterns of different sizes or by biaxial stretching on PDMS membrane increases the number of endoplasmic reticulum exit sites (ERES) and stimulates ER-export of a secretory marker (mannosidase II). They provide evidence that this effect is dependent of a minor pool of Rac1 interacting with Sar1, which is involved in the biogenesis of COPII vesicles. Overall, this is an interesting study that reveals an unexpected role of Rac1. The authors used a wide range of methodological approaches that support such a role. I have a few comments that should be addressed prior to publication: Response: We thank the reviewer for their positive comments and constructive criticism. 1) Fig. 1E. A clear increase in FRET signal of the Rac1 biosensor is observed after stretching. I am not sure what this experience means given that only a minor pool of Rac1 is associated with ERES. Response: We agree that the mechanically activated global Rac1 pool has other effects in cells in addition to signaling to ERES. Thus, we think that only a part of the mechanically activated Rac1 pool signals to ERES. To get an estimation of how big this pool might be, we tested the impact of the ER-anchored Rac1-GAP on total Rac1 activity. We observed that the reduction is in the range of 10-15% as shown in the new Fig.S4H. Of course, this is even an overestimation, because an ER-anchored Rac1-GAP might also affect Rac1 pools that are in close vicinity to the ER.  Fig. 1H are not convincing. Response: The ratio is approximately the same in 3G-H and 5G (now 5K). In Fig. 3G-H the ratio after 20 min is around 8. In Fig. 5G the ratio is measured at 20 min after biotin and has an average value of 6.5. This is generally within the normal variation. The ratio in Fig.1H (now Fig. 1J) is different than the ones in Fig. 3H and 5K because this experiment was done in a different way than the ones in Fig.3H and 5K. Firstly, the experiment in Figure 1H is a live cell imaging experiment where cells were grown on the PDMS membranes, while the ones in Figs. 3&5 are fixed cells grown on glass coverslips. Another difference is that the experiment in Figure 1H was imaged with an epifluorescence microscope equipped with a mercury lamp, while the experiments in Figs. 3&5 were imaged at a laser scanning confocal/spinning-disk microscopes. We are aware of this difference, but the overall trend is the same in both experiments. We think that the experiment in Fig.1H is a nice contribution to our manuscript. We understand the reviewer's concern because no Golgi marker was used. However, we used Mannosidase-II as a RUSH reporter, which is a Golgi protein. Hence, ManII will only traffic to the Golgi, and at the end of the RUSH experiment serve as an indicator for Golgi position. This can be appreciated from Fig. 3G, Fig.5C and J (timepoint 30 min). Furthermore, we did not use a RUSH reporter that traffics beyond the Golgi (such as VSVG), because in such a case the signal in the Golgi peaks (as the cargo enters the Golgi) and then drops (as the cargo leaves the Golgi). In the case of ManII, the signal increases in the Golgi region and then reaches a plateau. This makes assessing the arrival of Golgi residing cargos in RUSH experiments possible even in the absence of the Golgi markers. We have also modified Fig.1H (now Fig. 1J) to improve the data visualization for Fig.1H (now Fig. 1J). Finally, the inherent nature of PDMS membrane make live cell imaging (focusing issues) over time a challenging task, which is why an epifluorescence microscope was used and therefore colocalizations would anyway not have been possible. We very much hope to have convinced the reviewer to keep the data in Figure 1H as part of our manuscript.
3) Fig. 2C: it is shown that the depletion of Sec16A does not affect cell size. What about Sar1 depletion? Response: We performed the experiment asked by the reviewer and the new data is now shown in Fig. 2C, where we show that Sar1A/B depletion has no effect on cell size. The Sec16A knockdown and cell size data is now part of the supplementary Fig.S2G&H. Fig. 4G: The idea to activate Rac1 at the ER by optogenetics is nice but unfortunately the IF pictures provided are not very informative. Other pictures with an ER marker must be shown. Response: We used an ER-residing protein Sec61β to recruit TIAM to the ER. As recommended by the reviewer, we have now included Sec61β in the figure and show localization of both TIAM and Sec61β over time following the optogenetic recruitment. This is now shown in Fig.4I.

Response to Referee #2:
This manuscript reports control of secretory pathway by mechanical cues through a direct interaction of Rac1 and Sar1. This would represent a novel and exciting development in the field. There are many external and intrinsic cues that impact on secretory activity and while perhaps not surprising that mechanical strain plays a role, the mechanism here would provide a rally compelling and exciting advance. Sar1 controls the assembly of the COPII complex at the ER, Rac1 controls multiple levels of actin cytoskeleton remodeling at various points through the cell.
The key to the paper is whether indeed Sar1 and Rac1 do indeed interact and whether mechanical strain does indeed impact COPII function. Response: We thank the reviewer for their critical assessment of our manuscript and suggestions for improvement.
The data in Figure 1 seek to define an increase in ERES number caused by cell spreading. While this could be the case, it is equally possible that the pre-existing ERES are less well clustered and therefore more definable using the software. This has been shown previously in work on TFG for example. Indeed, that this change occurs within a small number of hours is challenging to reconcile with enhanced expression of COPII which would presumably be needed to account for this increase in ERES number (as happens for example in plasma cell differentiation). Response: We agree with the reviewer that the ERES increase is unlikely due to de novo synthesis of COPII, because of the short time frame of our experiments (few minutes to maximally 4 h). We thank the reviewer for raising this important point, which we have now discussed. Then there is the possibility of redistribution of ERES rather than a genuine increase. We think the increase in ERES number is genuine for two reasons: firstly, if the increase were not a real one, but only due to redistribution of ERES, then it would be expected to occur in any condition, irrespective of the biological context. However, we observe the increase only in control cells and not in Rac inhibited cells. Secondly, the increase of ERES is in line with the acceleration of ER-to-Golgi trafficking as observed in the RUSH assay. A mere redistribution will not cause a change in ER-to-Golgi trafficking. Therefore, we think that our conclusions and interpretations of these data is valid.
I think the work suffers from being done in HeLa cells here in which COPII seems very tightly clustered and difficult to resolve in terms of individual puncta. While other cell types have been used to validate outcomes later in the paper, it would be better to see well spread cells here. Also one is left to question the generality given that these are a cancer cell line -is there a relevance to hard versus soft tumors here? Response: In addition to HeLa cells, we had already used 2 other cell lines (PC3 and MDA-MB-231) to test the generality of our findings. In response to the reviewer's comment, we obtained new data from experiments carried out with mechanically challenged RPE-1 cells, which are non-transformed cells (Fig.1C, Fig.S1C-E), to further strengthen our results. In our experience, HeLa cells are well spread cells and we observe the juxtanuclear clustering of ERES in all cell lines we ever worked on (HeLa, HeLaK, HeLaS3, HEK239, HEK293T, MDA-MB-231, BT549, U2OS, PC3, primary fibroblasts, various multiple myeloma cells, and RPE-1). Most importantly, we can segment and count the juxtanuclear ERES (please see the image with overlaid count masks below). While an interesting topic, the investigations of how ERES adapt to soft and stiff substrates is beyond the scope of this work. Another highly relevant mechanical stress is compression, and we are planning to investigate this in the future. However, the current work focuses only on stretching as a mechanical stimulus.
I struggled to interpret some of Figure 2 and question the use of statistics here in 2B (my interpretation is that in all cases depletion of Sar1 still reduces cell spread irrespective of micropattern. I think it difficult to conclude that these data support that "the early secretory pathway is required for adaptation to mechanical strain" rather that it suggests the early secretory pathway is required for cell spreading (which is largely considered known from its central role in both matrix biogenesis, integrin trafficking, and general membrane dynamics). Sec16A is used as a key COPII protein here (2C) yet I saw no validation of Sec16A knockdown or indication of how the degree of knockdown is correlated with cell-by-cell outcomes. Incomplete depletion could explain these data. Response: We agree with the reviewer that our experiment shows how ERES regulate the ability of cells to spread, and we have added this phrase now to the text. However, we also think that the spread defect on a large micropattern also reflects a reduced ability of cells to adapt to mechanical stress. Spreading of cells on micropatterns is different that the spontaneous cell spreading. The reviewer has correctly pointed out that spontaneous spreading is something that happens mainly as a combination of internal forces in cells (e.g. actin) together with integrin and matrix deposition. However, spreading of cells on a micropattern is different from this, because cells are "forced" to adopt a geometry of certain size. Work by others showed that cells experience more tension at their cell surface when asked to cover a larger geometry. We think that the secretory pathway helps cells cope with this stress by controlling membrane supply. We agree with the reviewer that the secretory pathway controls membrane flux, but we are unaware of any previous paper where the effect of COPII on cell spreading on micropatterns was tested. To better convey this message and support this finding, we have added a new experiment. We reasoned that cells with reduced ERES function will exhibit more membrane damage when subjected to mechanical strain. To test this experimentally, we determined the membrane permeability of cells exposed to uniaxial stretch using propidium iodide. As shown in Fig. S2F, cells depleted of Sec16A become more permeable to propidium iodide 10-15 min after stretching. We hope that this clarification, as well as the new data increase the confidence of the reviewer in our data. The reviewer also questions the choice of statistical test: We chose to perform Chi-square test because of the qualitative nature of the experiment (a binary variable in "yes" or "no" format resulting from the question: do cells fully occupy the micropatterns?). In such cases, the Chi-square test is a very good choice, and we are confident that it is suitable.
A blot validating our Sec16 siRNA is now shown in Fig. S2G. We thank the reviewer for correcting this oversight.
The Rac inhibition work is questionable from the conclusions drawn, I am not convinced for example that the inhibition f Rac1 activity does indeed reduces ERES number. Also, I was surprised by the apparent reproducibility of some data -e.g. what is the consistent peak of activity at 20 mins in 3E pink line? If these are true averages from independent replicates one would not expect that. I was also not clear if the data in 3G were from stable cell linesexpression levels of such trafficking reporters can have a big impact on trafficking efficiency. Also, for robustness, such data should really include a restoration of function such as RNAi resistant Rac1. Also in terms of image processing -in "background subtraction" is the same parameter applied to all images in a data set (as it must be) or on a case-by case/per image "auto calculated" basis? If the latter, this will in my view invalidate the data. If uniformly applied how is the background calculated i.e. on which image? Response: We have tested a role for Rac1 in regulating ERES in several ways (with and without mechanical stimulus), and provide strong evidence that Rac1 regulates ERES. We show that: (i) Rac1 inhibition reduces ERES (ii) Rac1 knockdown reduces ERES (iii) Rac1 inhibition delays ER-to-Golgi trafficking (iv) Rac1 knockdown delays ER-to-Golgi trafficking (v) Rac1 inhibition does not affect ERES in Rac1-knockout cells (Fig. S3I&J), indicating an on-target effect (vi) Rac1 interacts with Sar1 (vii) In the presence of Rac1, we observe more active Sar1 Therefore, we are confident that our conclusion that Rac1 regulates ERES function is correct and convincing.
As for the issue of counting ERES, our lab has a strong expertise in counting ERES, which is well documented in several of our previously published papers. Regardless, we include two sample images where we have overlaid count masks on ERES.
We assume that the reviewer is referring to the pink line in Fig. 3H since Fig.3E shows FRAP-curve of GFP-Sec16A and the time scale is in seconds. We apologize that the error bars were not properly displayed because of our formatting and choice to display standard error of mean. We have now modified Fig.3H from line graph (previously) to scatter plot where we show raw data distribution (76 -104 cells in total from 3 independent experiments). The modified figure also shows mean and standard deviation. We hope this addresses the concern.
All RUSH assays in this manuscript are performed with stable cell lines. We apologize that this information was not clear from the figure legends. We have now updated our figure legends with this information wherever necessary. We had demonstrated in Fig.S3C-E that stable expression of siRNA resistant Rac1 renders the ERES in these cells resistant to siRNA. In addition, we have also performed NSC23766 washout experiments and show (Fig.3C&D) recovery of ERES in cells following the washout. We hope that this increases the confidence of the reviewer in our data. In terms of image processing, the background subtraction was carried out in ImageJ, where a rolling ball radius of 50 pixels was applied to all images in a data set. All images within an experiment were processed and analyzed in exact same way. We have now specified this in the methods section of the manuscript. I did not find the colocalization data in Figure 4 convincing. Rac1 might be on endosomes at ER-endosome contact sites or at points of actin-ER crossover. Even if one accepts "colocalization" 2 spots with partial overlap seems to low to explain significant impacts on cell function. How does this change under strain? The images also look overly processedraw data should be made available.
Response: In response to reviewer's concern, we carried out (results shown in Fig. S4C) a triple colocalization study using HeLa cells that contain endogenously tagged Rac1. We immunostained GFP-Rac1 HeLa cells with an endosomal marker (EEA1) and ERES marker Sec31A. We did observe (as previously shown by others) Rac1 on endosomes. We found that Rac1 that colocalizes with the endosomal marker EEA1, does not colocalize with ERES. This suggests that the endosomal pool of Rac1 is distinct from ERES. These data are shown in Figure S4C. The images shown in Fig.4A are SRRF images. We have not processed the image in anyway other than slightly adjust brightness and contrast. We had to perform SRRF imaging since the cytosolic background of Rac1 was masking the subtle pool of Rac1 at the ER. The imaging was performed on an Andor Dragonfly microscope that has the SRRF feature preinstalled (a feature that the company developed together with Ricardo Henriques, whose group described the SRRF imaging method). We constantly observed a small and a very rapid/transient pool of Rac1 at the ER. In response to the reviewer's question about the effect of mechanical stress on Rac1-Sar1 interaction, we performed BiFC experiment showing that cells on a large micropattern have more Rac1-Sar1 complexes than cells on a small micropattern.
What validation has been done of GFP-Rac1 as a reporter? Response: We assume that the reviewer is referring to the cells with endogenously tagged Rac1. After endogenous tagging, we performed a series of control experiments to validate the newly generated cell line as shown in Fig. S4A&B. We designed PCR primers spanning different regions and observed PCR fragments as expected (Fig. S4A left panel).
Importantly, Sanger sequencing result shows GFP-incorporation at the desired site ( Fig.  S4A right panel). Finally, we also transfected these cells with siRNA against Rac1 and obtained a clear a reduction of the GFP-Rac1 levels (Fig. S4B). These data show that the cells contain endogenously tagged Rac1.
In 4G and H again I would like to have been able to review the underpinning data. These changes seem small and no statistical test is applied. No indication is given of reproducibility either. Response: The quantification graph (previous 4G, now 4J) already shows raw data distribution. Perhaps this was not clear from the figure legend. An example image is shown now in Fig. S4I. We include counts/cell in the table below (this will also be made available as part of source data): When we run a paired t-test between t0 and t90, there is a statistical significant difference when comparing all cells measured. This has now been indicated in the quantification graph. The KDELR experiments are intriguing but incomplete -surely these need to be linked to assays of Rac activation? Also KDELR2 will cycle from the ER to the Golgi so will not "only act at the ER". Response: We agree that the construct is likely to cycle, but the main effect will be at the ER, because this is where the steady state localization of this construct is.
In response to the reviewer's comment, we performed a G-LISA assay and show that expression of the ER-anchored Rac1-GAP reduces the total cellular pool of active Rac1 by about 10-15%. This small, but reproducible effect, is in the range that we expected and show that we do not affect a bigger pool of Rac1 in cells.
My major concern lies with the interaction data -the modelling is nice but needs experimental support. That shown does not robustly provide this. In Figure 7 I am not convinced by the IP data owing to a lack of controls. Negative controls of other small GTP binding proteins, other COPII proteins etc must be included. Similarly in Fig 8 the gels are overcropped -full gels/blots must be shown and negative and indeed positive controls are essential here. The data hint at the possibility of an interaction but are not sufficient to support the strength of conclusions drawn. Response: We agree with the reviewer, and have therefore performed more control experiments. As requested, we included RhoA as an additional control in our coIP experiments and show that RhoA does not interact with Sar1 (Fig. 7F). Of note, we used our in silico modeling strategy to predict key amino acids in Rac1 that is important for its interaction with Sar1. The two predicted amino acid residues were arginine at position 163 and lysine at position166. We mutated these residues in Rac1 and observed a reduced Rac1-Sar1 interaction (Fig.7F). The uncropped blots are shown below as requested: Fig 8 is similarly unconvincing, not quantified, and lacks controls (e.g. Rho as a negative control, dominant negative and constitutively active Rac mutants, use of the Rac inhibitor). Response: A quantification of the budding assay is shown. We think that using GTPgS and GDP is better than using dominant negative, or constitutively active mutants. Therefore, we repeated the active Sar1 pulldown experiments in the presence of GTPgS and GDP (Fig. 8A). GTPgS will allow for high levels of Sar1 activation and consequently, no effect of Rac1 is observed. Likewise, using GDP also abolished any effect of Rac1 on Sar1 activation.
Concerns on the statistical data -in every case, the numbers of technical and biological replicates must be stated. In many cases the data are not compelling and "hidden" in histograms when the original data should be included and plots done as scatter/violin/etc. SEM is not appropriate here either -standard deviations should be shown in all cases (see https://rupress.org/jcb/article/177/1/7/34602/Error-bars-in-experimental-biology) The t-test is likely not appropriate at all as most of the data do not look normally distributed. A non-parametric test with multiple comparisons is likely more appropriate. Response: We used SDs as suggested by the reviewer and changed the graphical presentation of the figures to include individual data points.
I am sorry that I cannot be more positive about this work. The topic is very exciting and has significant potential for in vivo relevance. That said, the data do (at least not yet) sufficiently support the conclusions. Response: We hope that the new data and the amendments will convince the reviewer now that our work is a strong candidate.

Response to Referee #3:
This manuscript from the Farhan group addresses an important question in the secretion field. How cells regulate secretion at the level of ER exit sites (ERES) and other cellular structures remains poorly understood. In fact, even specific conditions that trigger regulation of secretion are not fully catalogued/documented. Mechanical stimulation is known to influence the plasma membrane (and endocytosis), cell growth and motility, all of which depend to some extent on secretion. Here, the authors probe the link between mechanical strain and secretion. The topic is exciting, and the findings are important. The main finding is that ERES abundance does indeed respond to mechanical stress, and that this is dependent on Rac1. The authors go on to show that Rac1 may play a more constitute role in ERES maintenance, and here there is a lost opportunity that would leverage the mechanical strain approaches developed in the first half of the study to reinforce the role for Rac1. Response: We thank the reviewer for recognizing the importance of our work and for providing constructive criticism.
1. On p. 3 the authors claim that the observed increase in ERES is not due to increase in volume/biomass. Although I appreciate the short time frame of the experiment, I'm not sure I understand the broader reasoning here. To substantiate this claim, the authors could measure cell volume as well as surface area and ERES number to demonstrate the relationships between these parameters more precisely. Response: We agree with the reviewer that we might have speculated too much here without actually demonstrating this point with the increase in biomass. We have therefore removed this statement from the text. To accurately show this, we would have had to perform proteomic and lipidomic experiments to show that the biomass of our cells has not changed.
2. Fig. 1E: the FRET sensor would be an excellent reporter to use in large vs. small cells to further substantiate the Rac1 effects. Response: We performed the experiment asked by the reviewer. As shown in Fig.1F, the FRET reporter indicates higher Rac1 activity in cells on a large micropattern than on a small micropattern corroborating the results obtained with mechanically stimulated cells grown on PDMS membranes.
3. The effect of Sar1 knockdown on cell spreading is profound. I was left wondering why Rac1 inhibition does not similarly cause cells to fully spread, especially if Rac1 activation lies upstream of Sar1 and its role in ERES. Response: We performed this experiment and show that inhibition of Rac1 phenocopies the Sar1 with respect to cell spreading. The data are part of Fig.2D&E.
4. The authors go on to show that Rac1 may play a more constitutive role in ERES maintenance/function. Here I felt there is room to leverage the tools to better probe the mechanical effects. For example, does KDELR-GAP overexpression abrogate stretching effects? Similarly, does CytoD/LatA treatment abrogate the stretch response, implying broader stretch effects beyond local Rac1? Finally, do Rac1/Sar1 BiFC puncta increase upon mechanical strain? Response: We overexpressed KDELR2-GAP and cultured these cells on micropatterns to quantitate ERES. We found that cells overexpressing KDELR2-GAP have less ERES when cultured on large micropattern (Fig.4G&H) similarly to the effect we observed with Rac1 inhibition shown in Fig.1. We also performed the second experiment the reviewer asked for, where we show that CytoD treated cells still respond by increasing ERES number when subjected to stretch (Fig.  5F&G). This result supports the notion that actin is not involved in mediating the observed Rac1 effect on ERES.
Finally, we also performed the third experiment the reviewer asked for and show that cells on a large micropattern have more Rac1/Sar1 BiFC puncta than cells on a small micropattern. This is to be expected because cells on large micropatterns have more ERES. These data are shown in Fig. 6E&F.
5. Controls for the Rac1-Sar1 BiFC experiment are missing (ie no fluorescence when each partner is expressed alone). Response: The requested controls are shown in Fig. S6A.
6. In Figure 7, the pulldowns showing Rac1/Sar1 interaction, and the "active Sar1" assay should include additional GDP and/or GMP-PNP controls to demonstrate nucleotide specificity. Response: We repeated the IP experiments in the present of GTPgS and GDP ( Figure 8A). GTPgS will allow for high levels of Sar1 activation and consequently, no effect of Rac1 is observed. Likewise, using GDP also abolished any effect of Rac1 on Sar1 activation. To further increase the confidence in our IP experiments, we also tested whether RhoA interacts with Sar1, and it did not. We also used modeling to predict two residues in Rac1 that could potentially mediate the interaction with Sar1. Mutation of these residues in Rac1 reduced the interaction with Sar1 as shown in Fig Thank you for submitting your manuscript for consideration by the EMBO Journal. It has now been seen for a second time by three referees whose comments are shown below.
As you will see you have addressed most of the referees' concerns to their satisfaction. However, referee 2 has some, I believe reasonable, residual concerns, especially over quantification and controls used in some of your Western blots. I therefore think it would be of general benefit to give you the opportunity to address these points. If you would like to have a quick Zoom call to go over the work, I will be available all next week.
Given the referees' positive recommendations, I would like to invite you to submit a revised version of the manuscript, addressing the comments of all three reviewers. I should add that it is EMBO Journal policy to allow only a single round of revision, and acceptance of your manuscript will therefore depend on the completeness of your responses in this revised version.
When preparing your letter of response to the referees' comments, please bear in mind that this will form part of the Review Process File, and will therefore be available online to the community. For more details on our Transparent Editorial Process, please visit our website: https://www.embopress.org/page/journal/14602075/authorguide#transparentprocess There is no doubt that the manuscript is much improved by the new data. However, I retain concerns on the colocalization data and interaction data. There remains an insufficient use of controls, notably in Figures 7 and 8. Blots e.g. 8B are saturated and not suitable for quantification and anyway ECL is only semi-quantitative. There are no controls in 8A -input? a small GTP binding protein that isn't impacts e.g. Rab1? Looking carefully at 7F Rac1 appears expressed at a higher level than the other proteins which could explain greater detection. This compromises the Rac1 KF/AA mutation data. The co-transfection approach here is not ideal -this should really be done with recombinant protein. In 8A these data require extensive repetition and quantification as surely addition of GTP or GTP-gamma-S will increase the population of "active" Sar1 in each experiment. I appreciate that the Rac1 lane acts as an internal control here but this is not in itself sufficient.
In terms of colocalization if one were to rotate the Sec61 channel, I am reasonably convinced that some "colocalization" would still be evident. Even Spot 2 indicates spots adjacent not overlapping. In other places the statistical testing does not support the conclusions e.g. 3D where the NSC washout has no effect compared to the adjacent column.
I simply don't think that the effect sizes support the strength of conclusions, particularly the title. Many of my original concerns remain.
Fundamentally, I do agree that there is something interesting going on here but I am not yet convinced that the data support a direct role for Rac1 in any ERES response to mechanical strain as claimed in the title.
Referee #3: The authors have satisfactorily addressed all of my concerns and I consider the revised manuscript fully acceptable for publication. One very minor addition concerns my previous point 4(c) about the Rac1/Sar1 BiFC puncta: my question was more about total fluorescence rather than number of spots. Of course, it's expected that the ERES number will go up because of the large cell effect, but I was curious as to whether the BiFC approach could be used to interpret an increase in the direct interaction between Sar1 and Rac1 upon stretching, which would further support the authors' claims. Not a big deal, but might be interesting to measure...

24th Jun 2022 2nd Authors' Response to Reviewers
As suggested by you, we have now changed a few things in our manuscript to have a better balance between data and conclusions. All changes are highlighted in purple color. We added a piece of discussion where we clearly state that while we think that the Rac1-Sar1 complex is specific, that future work will likely uncover other endomembrane functions for Rac1 via crosstalk with other small GTPases.
We also changed the initial part of the discussion to make it more balanced. We changed Figure 3D such that it now shows dots for all individual data points (i.e. cells) where the number of ERES has been counted. The calculated statistics are now significant and therefore supports the data.
Finally, we changed the title of the manuscript to a more conservative one: "Rac1 is a mechanosensitive regulator of ER exit sites". We think this title is now fully supported by the data and we think because it is short and catchy, that it will appeal to a broader readership. I hope the changes are satisfactory and that our work is now a candidate for publication in the EMBO Journal.

24th Jun 2022 2nd Revision -Editorial Decision
Dear Hesso, We have now received re-review reports from all three referees. You have addressed the concerns of the referees satisfactorily. However, I would like you to discuss in the manuscript the points of Referee 2 regarding the specificity of the Sar1-Rac1 interaction.
In addition, there are some remaining editorial points which need to be addressed. Would you therefore please: incorporate the edits made to the figure legends by Wiley staff in the "Data edited ms file" add a "Data Availability Section" include up to five key words update the Conflict of Interest Section according to the instructions on our website. Please note that Dr Roca-Cusachs is an EMBO Member.  Resources table could be uploaded as Table  EV1 include a panel label for Fig 6A. We encourage the publication of source data, particularly for electrophoretic gels and blots, with the aim of making primary data more accessible and transparent to the reader. It would be great if you could provide me with a PDF file per figure that contains the original, uncropped and unprocessed scans of all or key gels used in the figures. The PDF files should be labeled with the appropriate figure/panel number, and should have molecular weight markers; further annotation could be useful but is not essential. The PDF files will be published online with the article as supplementary "Source Data" files. Source Data can also include Excel tables to accompany your graphs. We anticipate that their inclusion will make your work more discoverable and useable to scientists in the future.
I would like to request you pay particular attention to the following figures: in Figures 6D and 8B, the middle lane is too closely cropped. Blots are too closely cropped. Please send the source data and, if possible, include more space around the images in Figure 7E the blots need to be provided at higher resolution Please also send the source data provide source data for Figure EV2F, EV6, EV2B and Figure 6E.
We include a synopsis of the paper (see http://emboj.embopress.org/). Please provide me with a general summary statement and 3-5 bullet points that capture the key findings of the paper. We also need a summary figure for the synopsis. The size should be 550 wide by  high (pixels). You can also use something from the figures if that is easier.
EMBO Press is an editorially independent publishing platform for the development of EMBO scientific publications.
Thank you again for the opportunity to consider your work for publication. I look forward to your revision.
Best wishes,

William
William Teale, PhD Editor The EMBO Journal w.teale@embojournal.org 1st Jul 2022 3rd Authors' Response to Reviewers Please find attached our revised manuscript that was originally entitled "Mechanical strain stimulates COPII-dependent trafficking via Rac1".
As suggested by you, we have now changed a few things in our manuscript to have a better balance between data and conclusions. All changes are highlighted in purple color. We added a piece of discussion where we clearly state that while we think that the Rac1-Sar1 complex is specific, that future work will likely uncover other endomembrane functions for Rac1 via crosstalk with other small GTPases.
We also changed the initial part of the discussion to make it more balanced.
We changed Figure 3D such that it now shows dots for all individual data points (i.e. cells) where the number of ERES has been counted. The calculated statistics are now significant and therefore supports the data.
We changed the title of the manuscript to a more conservative one: "Rac1 is a mechanosensitive regulator of ER exit sites". We think this title is now fully supported by the data and we think because it is short and catchy, that it will appeal to a broader readership.
Finally, we responded to all other editorial comments.
I hope the changes are satisfactory and that our work is now a candidate for publication in the EMBO Journal 5th Jul 2022 3rd Revision -Editorial Decision Dear Hesso, I am pleased to inform you that your manuscript has been accepted for publication in the EMBO Journal.
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